Package 'climaemet'

Title: Climate AEMET Tools
Description: Tools to download the climatic data of the Spanish Meteorological Agency (AEMET) directly from R using their API and create scientific graphs (climate charts, trend analysis of climate time series, temperature and precipitation anomalies maps, warming stripes graphics, climatograms, etc.).
Authors: Manuel Pizarro [aut, cph] , Diego Hernangómez [aut, cre] (<https://orcid.org/0000-0001-8457-4658>, rOpenSpain), Gema Fernández-Avilés [aut]
Maintainer: Diego Hernangómez <diego.hernangomezherrero@gmail.com>
License: GPL-3
Version: 1.2.1.9000
Built: 2024-02-06 21:21:35 UTC
Source: https://github.com/rOpenSpain/climaemet

Help Index


Install an AEMET API Key

Description

This function will store your AEMET API key on your local machine so it can be called securely without being stored in your code. After you have installed your key, it can be called any time by typing Sys.getenv("AEMET_API_KEY") and can be used in package functions by simply typing AEMET_API_KEY.

Alternatively, you can install the API Key manually:

Usage

aemet_api_key(apikey, overwrite = FALSE, install = FALSE)

Arguments

apikey

The API key provided to you from the AEMET formatted in quotes. A key can be acquired at https://opendata.aemet.es/centrodedescargas/inicio.

overwrite

If this is set to TRUE, it will overwrite an existing AEMET_API_KEY that you already have in local machine.

install

if TRUE, will install the key in your local machine for use in future sessions. Defaults to FALSE.

Value

None

Note

To locate your API Key on your local machine, run rappdirs::user_cache_dir("climaemet", "R").

See Also

Other aemet_auth: aemet_detect_api_key()

Examples

# Don't run these examples!

if (FALSE) {
  aemet_api_key("111111abc", install = TRUE)

  # You can check it with:
  Sys.getenv("AEMET_API_KEY")
}

if (FALSE) {
  # If you need to overwrite an existing key:
  aemet_api_key("222222abc", overwrite = TRUE, install = TRUE)

  # You can check it with:
  Sys.getenv("AEMET_API_KEY")
}

Daily/annual climatology values

Description

Get climatology values for a station or for all the available stations. Note that aemet_daily_period() and aemet_daily_period_all() are shortcuts of aemet_daily_clim().

Usage

aemet_daily_clim(
  station = "all",
  start = Sys.Date() - 7,
  end = Sys.Date(),
  verbose = FALSE,
  return_sf = FALSE,
  extract_metadata = FALSE
)

aemet_daily_period(
  station,
  start = as.integer(format(Sys.Date(), "%Y")),
  end = start,
  verbose = FALSE,
  return_sf = FALSE,
  extract_metadata = FALSE
)

aemet_daily_period_all(
  start = as.integer(format(Sys.Date(), "%Y")),
  end = start,
  verbose = FALSE,
  return_sf = FALSE,
  extract_metadata = FALSE
)

Arguments

station

Character string with station identifier code(s) (see aemet_stations()) or "all" for all the stations.

start, end

Character string with start and end date. See Details.

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

return_sf

Logical TRUE or FALSE. Should the function return an sf spatial object? If FALSE (the default value) it returns a tibble. Note that you need to have the sf package installed.

extract_metadata

Logical TRUE/FALSE. On TRUE the output is a tibble with the description of the fields. See also get_metadata_aemet().

Details

start and end parameters should be:

Value

A tibble or a sf object

API Key

You need to set your API Key globally using aemet_api_key().

See Also

aemet_api_key(), as.Date()

Other aemet_api_data: aemet_extremes_clim(), aemet_forecast_daily(), aemet_last_obs(), aemet_monthly, aemet_normal, aemet_stations()

Examples

library(tibble)
obs <- aemet_daily_clim(c("9434", "3195"))
glimpse(obs)

# Metadata
meta <- aemet_daily_clim(c("9434", "3195"), extract_metadata = TRUE)

glimpse(meta$campos)

Check if an AEMET API Key is present for the current session

Description

The function would detect if an API Key is available on this session:

Usage

aemet_detect_api_key(...)

Arguments

...

Ignored

Value

TRUE or FALSE

See Also

Other aemet_auth: aemet_api_key()

Examples

aemet_detect_api_key()

Extreme values for a station

Description

Get recorded extreme values for a station.

Usage

aemet_extremes_clim(
  station = NULL,
  parameter = "T",
  verbose = FALSE,
  return_sf = FALSE,
  extract_metadata = FALSE
)

Arguments

station

Character string with station identifier code(s) (see aemet_stations())

parameter

Character string as temperature ("T"), precipitation ("P") or wind ("V") parameter.

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

return_sf

Logical TRUE or FALSE. Should the function return an sf spatial object? If FALSE (the default value) it returns a tibble. Note that you need to have the sf package installed.

extract_metadata

Logical TRUE/FALSE. On TRUE the output is a tibble with the description of the fields. See also get_metadata_aemet().

Value

A tibble or a sf object

API Key

You need to set your API Key globally using aemet_api_key().

See Also

aemet_api_key()

Other aemet_api_data: aemet_daily_clim(), aemet_forecast_daily(), aemet_last_obs(), aemet_monthly, aemet_normal, aemet_stations()

Examples

library(tibble)
obs <- aemet_extremes_clim(c("9434", "3195"))
glimpse(obs)

Forecast database by municipality

Description

Get a database of daily or hourly weather forecasts for a given municipality.

Usage

aemet_forecast_daily(x, verbose = FALSE, extract_metadata = FALSE)

aemet_forecast_hourly(x, verbose = FALSE, extract_metadata = FALSE)

Arguments

x

A vector of municipality codes to extract. For convenience, climaemet provides this data on the dataset aemet_munic (see municipio field) as of January 2020.

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

extract_metadata

Logical TRUE/FALSE. On TRUE the output is a tibble with the description of the fields. See also get_metadata_aemet().

Details

Forecasts format provided by the AEMET API have a complex structure. Although climaemet returns a tibble, each forecasted value is provided as a nested tibble. aemet_forecast_tidy() helper function can unnest these values an provide a single unnested tibble for the requested variable.

If extract_metadata = TRUE a simple tibble describing the value of each field of the forecast is returned.

Value

A nested tibble. Forecasted values can be extracted with aemet_forecast_tidy(). See also Details.

API Key

You need to set your API Key globally using aemet_api_key().

See Also

aemet_munic for municipality codes.

Other aemet_api_data: aemet_daily_clim(), aemet_extremes_clim(), aemet_last_obs(), aemet_monthly, aemet_normal, aemet_stations()

Other forecasts: aemet_forecast_tidy()

Examples

# Select a city
data("aemet_munic")
library(dplyr)
munis <- aemet_munic %>%
  filter(municipio_nombre %in% c(
    "Santiago de Compostela",
    "Lugo"
  )) %>%
  pull(municipio)

daily <- aemet_forecast_daily(munis)

# Metadata
meta <- aemet_forecast_daily(munis, extract_metadata = TRUE)
glimpse(meta$campos)

# Vars available
aemet_forecast_vars_available(daily)


# This is nested
daily %>%
  select(municipio, fecha, nombre, temperatura)

# Select and unnest
daily_temp <- aemet_forecast_tidy(daily, "temperatura")

# This is not
daily_temp

# Wrangle and plot
daily_temp_end <- daily_temp %>%
  select(
    elaborado, fecha, municipio, nombre, temperatura_minima,
    temperatura_maxima
  ) %>%
  tidyr::pivot_longer(cols = contains("temperatura"))

# Plot
library(ggplot2)
ggplot(daily_temp_end) +
  geom_line(aes(fecha, value, color = name)) +
  facet_wrap(~nombre, ncol = 1) +
  scale_color_manual(
    values = c("red", "blue"),
    labels = c("max", "min")
  ) +
  scale_x_date(
    labels = scales::label_date_short(),
    breaks = "day"
  ) +
  scale_y_continuous(
    labels = scales::label_comma(suffix = "º")
  ) +
  theme_minimal() +
  labs(
    x = "", y = "",
    color = "",
    title = "Forecast: 7-day temperature",
    subtitle = paste(
      "Forecast produced on",
      format(daily_temp_end$elaborado[1], usetz = TRUE)
    )
  )

Helper functions for extracting forecasts

Description

Helpers for aemet_forecast_daily() and aemet_forecast_hourly():

Usage

aemet_forecast_tidy(x, var)

aemet_forecast_vars_available(x)

Arguments

x

A database extracted with aemet_forecast_daily() or aemet_forecast_hourly().

var

Name of the desired var to extract

Value

A vector of characters (aemet_forecast_vars_available()) or a tibble (aemet_forecast_tidy()).

See Also

Other forecasts: aemet_forecast_daily()

Examples

# Hourly values
hourly <- aemet_forecast_hourly(c("15030", "28080"))

# Vars available
aemet_forecast_vars_available(hourly)

# Get temperature
temp <- aemet_forecast_tidy(hourly, "temperatura")

library(dplyr)
# Make hour - Need lubridate to adjust timezones
temp_end <- temp %>%
  mutate(
    forecast_time = lubridate::force_tz(
      as.POSIXct(fecha) + hora,
      tz = "Europe/Madrid"
    )
  )

# Add also sunset and sunrise
suns <- temp_end %>%
  select(nombre, fecha, orto, ocaso) %>%
  distinct_all() %>%
  group_by(nombre) %>%
  mutate(
    ocaso_end = lubridate::force_tz(
      as.POSIXct(fecha) + ocaso,
      tz = "Europe/Madrid"
    ),
    orto_end = lubridate::force_tz(
      as.POSIXct(fecha) + orto,
      tz = "Europe/Madrid"
    ),
    orto_lead = lead(orto_end)
  ) %>%
  tidyr::drop_na()



# Plot

library(ggplot2)

ggplot(temp_end) +
  geom_rect(data = suns, aes(
    xmin = ocaso_end, xmax = orto_lead,
    ymin = min(temp_end$temperatura),
    ymax = max(temp_end$temperatura)
  ), alpha = .4) +
  geom_line(aes(forecast_time, temperatura), color = "blue4") +
  facet_wrap(~nombre, nrow = 2) +
  scale_x_datetime(labels = scales::label_date_short()) +
  scale_y_continuous(labels = scales::label_number(suffix = "º")) +
  labs(
    x = "", y = "",
    title = "Forecast: Temperature",
    subtitle = paste("Forecast produced on", format(temp_end$elaborado[1],
      usetz = TRUE
    ))
  )

Last observation values for a station

Description

Get last observation values for a station.

Usage

aemet_last_obs(
  station = "all",
  verbose = FALSE,
  return_sf = FALSE,
  extract_metadata = FALSE
)

Arguments

station

Character string with station identifier code(s) (see aemet_stations()) or "all" for all the stations.

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

return_sf

Logical TRUE or FALSE. Should the function return an sf spatial object? If FALSE (the default value) it returns a tibble. Note that you need to have the sf package installed.

extract_metadata

Logical TRUE/FALSE. On TRUE the output is a tibble with the description of the fields. See also get_metadata_aemet().

Value

A tibble or a sf object

API Key

You need to set your API Key globally using aemet_api_key().

See Also

Other aemet_api_data: aemet_daily_clim(), aemet_extremes_clim(), aemet_forecast_daily(), aemet_monthly, aemet_normal, aemet_stations()

Examples

library(tibble)
obs <- aemet_last_obs(c("9434", "3195"))
glimpse(obs)

Monthly/annual climatology

Description

Get monthly/annual climatology values for a station or all the stations. aemet_monthly_period() and aemet_monthly_period_all() allows requests that span several years.

Usage

aemet_monthly_clim(
  station = NULL,
  year = as.integer(format(Sys.Date(), "%Y")),
  verbose = FALSE,
  return_sf = FALSE,
  extract_metadata = FALSE
)

aemet_monthly_period(
  station = NULL,
  start = as.integer(format(Sys.Date(), "%Y")),
  end = start,
  verbose = FALSE,
  return_sf = FALSE,
  extract_metadata = FALSE
)

aemet_monthly_period_all(
  start = as.integer(format(Sys.Date(), "%Y")),
  end = start,
  verbose = FALSE,
  return_sf = FALSE,
  extract_metadata = FALSE
)

Arguments

station

Character string with station identifier code(s) (see aemet_stations())

year

Numeric value as date (format: YYYY).

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

return_sf

Logical TRUE or FALSE. Should the function return an sf spatial object? If FALSE (the default value) it returns a tibble. Note that you need to have the sf package installed.

extract_metadata

Logical TRUE/FALSE. On TRUE the output is a tibble with the description of the fields. See also get_metadata_aemet().

start

Numeric value as start year (format: YYYY).

end

Numeric value as end year (format: YYYY).

Value

A tibble or a sf object

API Key

You need to set your API Key globally using aemet_api_key().

See Also

Other aemet_api_data: aemet_daily_clim(), aemet_extremes_clim(), aemet_forecast_daily(), aemet_last_obs(), aemet_normal, aemet_stations()

Examples

library(tibble)
obs <- aemet_monthly_clim(station = c("9434", "3195"), year = 2000)
glimpse(obs)

Data set with all the municipalities of Spain

Description

A tibble with all the municipalities of Spain as defined by the INE (Instituto Nacional de Estadistica) as of January 2020.

Format

A tibble with 8,131 rows and fields:

municipio

INE code of the municipality.

municipio_nombre

INE name of the municipality.

cpro

INE code of the province.

cpro_nombre

INE name of the province.

codauto

INE code of the autonomous community.

codauto_nombre

INE code of the autonomous community.

Source

INE, Municipality codes by province

See Also

aemet_forecast_daily(), aemet_forecast_hourly()

Other dataset: climaemet_9434_climatogram, climaemet_9434_temp, climaemet_9434_wind

Examples

data(aemet_munic)

aemet_munic

Normal climatology values

Description

Get normal climatology values for a station (or all the stations with aemet_normal_clim_all(). Standard climatology from 1981 to 2010.

Usage

aemet_normal_clim(
  station = NULL,
  verbose = FALSE,
  return_sf = FALSE,
  extract_metadata = FALSE
)

aemet_normal_clim_all(
  verbose = FALSE,
  return_sf = FALSE,
  extract_metadata = FALSE
)

Arguments

station

Character string with station identifier code(s) (see aemet_stations()) or "all" for all the stations.

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

return_sf

Logical TRUE or FALSE. Should the function return an sf spatial object? If FALSE (the default value) it returns a tibble. Note that you need to have the sf package installed.

extract_metadata

Logical TRUE/FALSE. On TRUE the output is a tibble with the description of the fields. See also get_metadata_aemet().

Value

A tibble or a sf object

API Key

You need to set your API Key globally using aemet_api_key().

Note

Code modified from project https://github.com/SevillaR/aemet

See Also

Other aemet_api_data: aemet_daily_clim(), aemet_extremes_clim(), aemet_forecast_daily(), aemet_last_obs(), aemet_monthly, aemet_stations()

Examples

library(tibble)
obs <- aemet_normal_clim(c("9434", "3195"))
glimpse(obs)

AEMET stations

Description

Get AEMET stations.

Usage

aemet_stations(verbose = FALSE, return_sf = FALSE)

Arguments

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

return_sf

Logical TRUE or FALSE. Should the function return an sf spatial object? If FALSE (the default value) it returns a tibble. Note that you need to have the sf package installed.

Details

The first result of the API call on each session is (temporarily) cached in the assigned tempdir() for avoiding unneeded API calls.

Value

A tibble or a sf object

API Key

You need to set your API Key globally using aemet_api_key().

Note

Code modified from project https://github.com/SevillaR/aemet

See Also

Other aemet_api_data: aemet_daily_clim(), aemet_extremes_clim(), aemet_forecast_daily(), aemet_last_obs(), aemet_monthly, aemet_normal

Examples

library(tibble)
stations <- aemet_stations()
stations

# Cached during this R session
stations2 <- aemet_stations(verbose = TRUE)

identical(stations, stations2)

Climatogram data for Zaragoza Airport ("9434") period 1981-2010

Description

Normal data for Zaragoza Airport (1981-2010). This is an example dataset used to plot climatograms.

Format

A data.frame with columns 1 to 12 (months) and rows:

p_mes_md

Precipitation (mm).

tm_max_md

Maximum temperature (Celsius).

tm_min_md

Minimum temperature (Celsius).

ta_min_md

Absolute monthly minimum temperature (Celsius).

Source

AEMET.

See Also

ggclimat_walter_lieth(), climatogram_period(), climatogram_normal()

Other dataset: aemet_munic, climaemet_9434_temp, climaemet_9434_wind

Other climatogram: climatogram_normal(), climatogram_period(), ggclimat_walter_lieth()

Examples

data(climaemet_9434_climatogram)

Average annual temperatures for Zaragoza Airport ("9434") period 1950-2020

Description

Yearly observations of average temperature for Zaragoza Airport (1950-2020). This is an example dataset.

Format

A tibble with columns:

year

Year of reference.

indicativo

Identifier of the station.

temp

Average temperature (Celsius).

Source

AEMET.

See Also

Other dataset: aemet_munic, climaemet_9434_climatogram, climaemet_9434_wind

Other stripes: climatestripes_station(), ggstripes()

Examples

data(climaemet_9434_temp)

Wind conditions for Zaragoza Airport ("9434") period 2000-2020

Description

Daily observations of wind speed and directions for Zaragoza Airport (2000-2020). This is an example dataset.

Format

A tibble with columns:

fecha

Date of observation.

dir

Wind directions (0-360).

velmedia

Average wind speed (km/h)

Source

AEMET.

See Also

Other dataset: aemet_munic, climaemet_9434_climatogram, climaemet_9434_temp

Other wind: ggwindrose(), windrose_days(), windrose_period()

Examples

data(climaemet_9434_wind)

climaemet_news

Description

Show the NEWS file of the climaemet package.

Usage

climaemet_news()

Details

(See description)

Value

Open NEWS from climaemet.

See Also

Other helpers: dms2decdegrees(), first_day_of_year()

Examples

## Not run: 
climaemet_news()

## End(Not run)

Station climate stripes graph

Description

Plot climate stripes graph for a station

Usage

climatestripes_station(
  station,
  start = 1950,
  end = 2020,
  with_labels = "yes",
  verbose = FALSE,
  ...
)

Arguments

station

Character string with station identifier code(s) (see aemet_stations())

start

Numeric value as start year (format: YYYY).

end

Numeric value as end year (format: YYYY).

with_labels

Character string as yes/no. Indicates whether to use labels for the graph or not.

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

...

Arguments passed on to ggstripes

n_temp

Numeric value as the number of colors of the palette. (default 11).

col_pal

Character string indicating the name of the hcl.pals() color palette to be used for plotting.

Value

A ggplot2 object

API Key

You need to set your API Key globally using aemet_api_key().

See Also

ggstripes()

Other aemet_plots: climatogram_normal(), climatogram_period(), ggclimat_walter_lieth(), ggstripes(), ggwindrose(), windrose_days(), windrose_period()

Other stripes: climaemet_9434_temp, ggstripes()

Examples

climatestripes_station(
  "9434",
  start = 2010,
  end = 2020,
  with_labels = "yes",
  col_pal = "Inferno"
)

Walter & Lieth climatic diagram from normal climatology values

Description

Plot of a Walter & Lieth climatic diagram from normal climatology data for a station. This climatogram are great for showing a summary of climate conditions for a place over a time period (1981-2010).

Usage

climatogram_normal(
  station,
  labels = "en",
  verbose = FALSE,
  ggplot2 = TRUE,
  ...
)

Arguments

station

Character string with station identifier code(s) (see aemet_stations())

labels

Character string as month labels for the X axis: "en" (english), "es" (spanish), "fr" (french), etc.

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

ggplot2

TRUE/FALSE. On TRUE the function uses ggclimat_walter_lieth(), if FALSE uses climatol::diagwl().

...

Further arguments to climatol::diagwl() or ggclimat_walter_lieth(), depending on the value of ggplot2

Value

A plot.

API Key

You need to set your API Key globally using aemet_api_key().

Note

The code is based on code from the CRAN package climatol

References

See Also

Other aemet_plots: climatestripes_station(), climatogram_period(), ggclimat_walter_lieth(), ggstripes(), ggwindrose(), windrose_days(), windrose_period()

Other climatogram: climaemet_9434_climatogram, climatogram_period(), ggclimat_walter_lieth()

Examples

climatogram_normal("9434")

Walter & Lieth climatic diagram for a time period

Description

Plot of a Walter & Lieth climatic diagram from monthly climatology data for a station. This climatogram are great for showing a summary of climate conditions for a place over a specific time period.

Usage

climatogram_period(
  station = NULL,
  start = 1990,
  end = 2020,
  labels = "en",
  verbose = FALSE,
  ggplot2 = TRUE,
  ...
)

Arguments

station

Character string with station identifier code(s) (see aemet_stations())

start

Numeric value as start year (format: YYYY).

end

Numeric value as end year (format: YYYY).

labels

Character string as month labels for the X axis: "en" (english), "es" (spanish), "fr" (french), etc.

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

ggplot2

TRUE/FALSE. On TRUE the function uses ggclimat_walter_lieth(), if FALSE uses climatol::diagwl().

...

Further arguments to climatol::diagwl() or ggclimat_walter_lieth(), depending on the value of ggplot2

Value

A plot.

API Key

You need to set your API Key globally using aemet_api_key().

Note

The code is based on code from the CRAN package climatol

References

See Also

Other aemet_plots: climatestripes_station(), climatogram_normal(), ggclimat_walter_lieth(), ggstripes(), ggwindrose(), windrose_days(), windrose_period()

Other climatogram: climaemet_9434_climatogram, climatogram_normal(), ggclimat_walter_lieth()

Examples

climatogram_period("9434", start = 2015, end = 2020, labels = "en")

Converts dms to decimal degrees

Description

Converts degrees, minutes and seconds to decimal degrees.

Usage

dms2decdegrees(input = NULL)

Arguments

input

Character string as DMS coordinates.

Value

A numeric value.

Note

Code modified from project https://github.com/SevillaR/aemet

See Also

Other helpers: climaemet_news(), first_day_of_year()

Examples

dms2decdegrees("055245W")

First and last day of year

Description

Get first and last day of year.

Usage

first_day_of_year(year = NULL)

last_day_of_year(year = NULL)

Arguments

year

Numeric value as year (format: YYYY).

Value

Character string as date (format: YYYY-MM-DD).

See Also

Other helpers: climaemet_news(), dms2decdegrees()

Examples

first_day_of_year(2000)
last_day_of_year(2020)

Client tool for AEMET API

Description

Client tool to get data and metadata from AEMET and convert json to tibble.

Usage

get_data_aemet(apidest, verbose = FALSE)

get_metadata_aemet(apidest, verbose = FALSE)

Arguments

apidest

Character string as destination URL. See https://opendata.aemet.es/dist/index.html.

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

Value

A tibble (if possible) or the results of the query as provided by httr2::resp_body_raw() or httr2::resp_body_string().

Source

https://opendata.aemet.es/dist/index.html

See Also

Some examples on how to use these functions on vignette("extending-climaemet").

Examples

# Run this example only if AEMET_API_KEY is detected

url <- "/api/valores/climatologicos/inventarioestaciones/todasestaciones"

get_data_aemet(url)


# Metadata

get_metadata_aemet(url)

# We can get data from any API endpoint

# Plain text

plain <- get_data_aemet("/api/prediccion/nacional/hoy")

cat(plain)

# An image

image <- get_data_aemet("/api/mapasygraficos/analisis")

# Write and read
tmp <- tempfile(fileext = ".gif")

writeBin(image, tmp)

gganimate::gif_file(tmp)

Walter and Lieth climatic diagram on ggplot2

Description

Plot of a Walter and Lieth climatic diagram of a station. This function is an updated version of climatol::diagwl(), by Jose A. Guijarro.

[Experimental]

Usage

ggclimat_walter_lieth(
  dat,
  est = "",
  alt = NA,
  per = NA,
  mlab = "es",
  pcol = "#002F70",
  tcol = "#ff0000",
  pfcol = "#9BAEE2",
  sfcol = "#3C6FC4",
  shem = FALSE,
  p3line = FALSE,
  ...
)

Arguments

dat

Monthly climatic data for which the diagram will be plotted.

est

Name of the climatological station

alt

Altitude of the climatological station

per

Period on which the averages have been computed

mlab

Month labels for the X axis. Use 2-digit language code ("en", "es", etc.). See readr::locale() for info.

pcol

Color pen for precipitation.

tcol

Color pen for temperature.

pfcol

Fill color for probable frosts.

sfcol

Fill color for sure frosts.

shem

Set to TRUE for southern hemisphere stations.

p3line

Set to TRUE to draw a supplementary precipitation line referenced to three times the temperature (as suggested by Bogdan Rosca).

...

Other graphic parameters

Details

See Details on climatol::diagwl().

Climatic data must be passed as a 4x12 matrix or data.frame of monthly (January to December) data, in the following order:

See climaemet_9434_climatogram for a sample dataset.

Value

A ggplot2 object. See help("ggplot2").

API Key

You need to set your API Key globally using aemet_api_key().

References

See Also

climatol::diagwl(), readr::locale()

Other aemet_plots: climatestripes_station(), climatogram_normal(), climatogram_period(), ggstripes(), ggwindrose(), windrose_days(), windrose_period()

Other climatogram: climaemet_9434_climatogram, climatogram_normal(), climatogram_period()

Examples

library(ggplot2)

wl <- ggclimat_walter_lieth(
  climaemet::climaemet_9434_climatogram,
  alt = "249",
  per = "1981-2010",
  est = "Zaragoza Airport"
)

wl

# As it is a ggplot object we can modify it

wl + theme(
  plot.background = element_rect(fill = "grey80"),
  panel.background = element_rect(fill = "grey70"),
  axis.text.y.left = element_text(
    colour = "black",
    face = "italic"
  ),
  axis.text.y.right = element_text(
    colour = "black",
    face = "bold"
  )
)

Warming stripes graph

Description

Plot different "climate stripes" or "warming stripes" using ggplot2. This graphics are visual representations of the change in temperature as measured in each location over the past 70-100+ years. Each stripe represents the temperature in that station averaged over a year.

Usage

ggstripes(
  data,
  plot_type = "stripes",
  plot_title = "",
  n_temp = 11,
  col_pal = "RdBu",
  ...
)

Arguments

data

a data.frame with date(year) and temperature(temp) variables.

plot_type

plot type (with labels, background, stripes with line trend and animation). Accepted values are "background", "stripes", "trend" or "animation".

plot_title

character string to be used for the graph title.

n_temp

Numeric value as the number of colors of the palette. (default 11).

col_pal

Character string indicating the name of the hcl.pals() color palette to be used for plotting.

...

further arguments passed to ggplot2::theme().

Value

A ggplot2 object

API Key

You need to set your API Key globally using aemet_api_key().

Note

"Warming stripes" charts are a conceptual idea of Professor Ed Hawkins (University of Reading) and are specifically designed to be as simple as possible and alert about risks of climate change. For more details see ShowYourStripes.

See Also

climatestripes_station(), ggplot2::theme() for more possible arguments to pass to ggstripes.

Other aemet_plots: climatestripes_station(), climatogram_normal(), climatogram_period(), ggclimat_walter_lieth(), ggwindrose(), windrose_days(), windrose_period()

Other stripes: climaemet_9434_temp, climatestripes_station()

Examples

library(ggplot2)

data <- climaemet::climaemet_9434_temp

ggstripes(data, plot_title = "Zaragoza Airport") +
  labs(subtitle = "(1950-2020)")

ggstripes(data, plot_title = "Zaragoza Airport", plot_type = "trend") +
  labs(subtitle = "(1950-2020)")

Windrose (speed/direction) diagram

Description

Plot a windrose showing the wind speed and direction using ggplot2.

Usage

ggwindrose(
  speed,
  direction,
  n_directions = 8,
  n_speeds = 5,
  speed_cuts = NA,
  col_pal = "GnBu",
  legend_title = "Wind speed (m/s)",
  calm_wind = 0,
  n_col = 1,
  facet = NULL,
  plot_title = "",
  ...
)

Arguments

speed

Numeric vector of wind speeds.

direction

Numeric vector of wind directions.

n_directions

Numeric value as the number of direction bins to plot (petals on the rose). The number of directions defaults to 8.

n_speeds

Numeric value as the number of equally spaced wind speed bins to plot. This is used if speed_cuts is NA (default 5).

speed_cuts

Numeric vector containing the cut points for the wind speed intervals, or NA (default).

col_pal

Character string indicating the name of the hcl.pals() color palette to be used for plotting.

legend_title

Character string to be used for the legend title.

calm_wind

Numeric value as the upper limit for wind speed that is considered calm (default 0).

n_col

The number of columns of plots (default 1).

facet

Character or factor vector of the facets used to plot the various windroses.

plot_title

Character string to be used for the plot title.

...

further arguments (ignored).

Value

A ggplot2 object

API Key

You need to set your API Key globally using aemet_api_key().

See Also

ggplot2::theme() for more possible arguments to pass to ggwindrose.

Other aemet_plots: climatestripes_station(), climatogram_normal(), climatogram_period(), ggclimat_walter_lieth(), ggstripes(), windrose_days(), windrose_period()

Other wind: climaemet_9434_wind, windrose_days(), windrose_period()

Examples

library(ggplot2)

speed <- climaemet::climaemet_9434_wind$velmedia
direction <- climaemet::climaemet_9434_wind$dir

rose <- ggwindrose(
  speed = speed,
  direction = direction,
  speed_cuts = seq(0, 16, 4),
  legend_title = "Wind speed (m/s)",
  calm_wind = 0,
  n_col = 1,
  plot_title = "Zaragoza Airport"
)
rose + labs(
  subtitle = "2000-2020",
  caption = "Source: AEMET"
)

Windrose (speed/direction) diagram of a station over a days period

Description

Plot a windrose showing the wind speed and direction for a station over a days period.

Usage

windrose_days(
  station,
  start = "2000-12-01",
  end = "2000-12-31",
  n_directions = 8,
  n_speeds = 5,
  speed_cuts = NA,
  col_pal = "GnBu",
  calm_wind = 0,
  legend_title = "Wind Speed (m/s)",
  verbose = FALSE
)

Arguments

station

Character string with station identifier code(s) (see aemet_stations()) or "all" for all the stations.

start

Character string as start date (format: YYYY-MM-DD).

end

Character string as end date (format: YYYY-MM-DD).

n_directions

Numeric value as the number of direction bins to plot (petals on the rose). The number of directions defaults to 8.

n_speeds

Numeric value as the number of equally spaced wind speed bins to plot. This is used if speed_cuts is NA (default 5).

speed_cuts

Numeric vector containing the cut points for the wind speed intervals, or NA (default).

col_pal

Character string indicating the name of the hcl.pals() color palette to be used for plotting.

calm_wind

Numeric value as the upper limit for wind speed that is considered calm (default 0).

legend_title

Character string to be used for the legend title.

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

Value

A ggplot2 object

API Key

You need to set your API Key globally using aemet_api_key().

See Also

aemet_daily_clim()

Other aemet_plots: climatestripes_station(), climatogram_normal(), climatogram_period(), ggclimat_walter_lieth(), ggstripes(), ggwindrose(), windrose_period()

Other wind: climaemet_9434_wind, ggwindrose(), windrose_period()

Examples

windrose_days("9434",
  start = "2000-12-01",
  end = "2000-12-31",
  speed_cuts = 4
)

Windrose (speed/direction) diagram of a station over a time period

Description

Plot a windrose showing the wind speed and direction for a station over a time period.

Usage

windrose_period(
  station,
  start = 2000,
  end = 2010,
  n_directions = 8,
  n_speeds = 5,
  speed_cuts = NA,
  col_pal = "GnBu",
  calm_wind = 0,
  legend_title = "Wind Speed (m/s)",
  verbose = FALSE
)

Arguments

station

Character string with station identifier code(s) (see aemet_stations()) or "all" for all the stations.

start

Numeric value as start year (format: YYYY).

end

Numeric value as end year (format: YYYY).

n_directions

Numeric value as the number of direction bins to plot (petals on the rose). The number of directions defaults to 8.

n_speeds

Numeric value as the number of equally spaced wind speed bins to plot. This is used if speed_cuts is NA (default 5).

speed_cuts

Numeric vector containing the cut points for the wind speed intervals, or NA (default).

col_pal

Character string indicating the name of the hcl.pals() color palette to be used for plotting.

calm_wind

Numeric value as the upper limit for wind speed that is considered calm (default 0).

legend_title

Character string to be used for the legend title.

verbose

Logical TRUE/FALSE. Provides information about the flow of information between the client and server.

Value

A ggplot2 object

API Key

You need to set your API Key globally using aemet_api_key().

See Also

aemet_daily_period()

Other aemet_plots: climatestripes_station(), climatogram_normal(), climatogram_period(), ggclimat_walter_lieth(), ggstripes(), ggwindrose(), windrose_days()

Other wind: climaemet_9434_wind, ggwindrose(), windrose_days()

Examples

windrose_period("9434",
  start = 2000, end = 2010,
  speed_cuts = 4
)